With the Shift-Up series thus far, we have explored the importance of testing and thinking as a customer. The basic premise is that we need to add another dimension to Quality Assurance other than Shift-Left and Shift-Right. This new dimension focuses on how your customer is actually using your application and if the intersection of your application, customer behavior, and your company’s business objectives all align.

To keep up with DevOps, testing and QA teams typically adopt a shift-up approach to move quality further up the software development lifecycle. The goal is to complete system testing, integration testing, and user acceptance testing (UAT) to ensure a bug-free release. While product quality has a direct correlation to increased revenue and positive business outcomes, this isn’t enough in the 21st-century marketplace. QA’s job isn’t just to de-risk applications by finding defects earlier but to help de-risk business strategy and potential problems with your user base by reporting customer experience defects.

Providing an amazing customer experience is critical in the travel and hospitality sector. Competition is fierce and consumers are fickle. If one website fails to deliver a slick, easy-to-use online interface, an alternative is only a couple of clicks away.

Customer experience transformation is a key initiative for any business that wants to position itself for the 21st century. Two important concepts involve updating and digitizing technology, and creating persistent customer relationships. According to Bain & Company, customer experience transformation starts with “… simplifying your core business and digitizing it where it matters.” McKinsey & Company writes that in any customer experience transformation, “… the voice of the customer can be used to identify upstream and cross-functional issues and address the root causes of problems.” In short, to see positive results, you need well-tested, high-quality digital assets that reflect ever-evolving customer needs and desires.

The weather, the tennis, the football — with all the distractions, you’d think those of us on the Real User Monitoring team would be kicking our feet up, right? Not a chance! I'm super excited to tell you about our latest release: a brand-new version of our Performance Trends Report.

Some of my customers are trying to design an automated script to perform specific workflows with a predicted outcome. Unfortunately, the automated workflow they want to execute has many variations in their environment, and they’re having trouble creating a dynamic, automated script that handles environment deviation.

This is Michael's third blog in his Shift Up series. You can read the first blog here and second blog here.

On May 21, 2018, Bank of America announced that it was rolling out its chatbot, Erica, to all its mobile customers. On the surface, the premise makes sense. It’s making the bank more relatable. It’s providing real-time customer support to people where artificial intelligence (AI) assistants like Siri and Alexa are becoming the norm. It doesn’t have the limitations that some phone-based IVRs have, and it aims to provide immediate assistance instead of making us wait for a human (we’ve all shouted “representative” or pressed zero dozens of times to get a real person). Erica is a great way for Bank of America to optimize the customer experience.

But let’s pull back the covers and ask some basic questions. How does Erica know the customer so well? How does Erica pull from different sources of information? How does Erica know what products and services to offer? What systems, both homegrown and third party, does Erica need to be effective?

Quality assurance (QA) used to be a compliance activity. You were releasing a product and needed to test it and stamp it “approved.” QA was about testing that the code worked. You might manually test the code. You might have even tried some automation — coding a set of test scripts that would try to capture regressions or errors that you had eradicated in the past, but which somehow crept back in. All in all, you were reasonably satisfied that you achieved a level of test coverage that met your goals. Then, you put your code into production and crossed your fingers that nothing went wrong. And if it did, you tried to fix it as quickly as humanly possible.

Everything about software has changed—how it’s architected, developed and produced, what it does, what users want from it, and how often they expect new features. To keep up, organisations are turning to continuous delivery and DevOps. Yet product teams still do a lot of manual testing, which consumes a lot of time they don’t have, thanks to shrinking test windows. Incorporating automation into your testing approach is a great strategy, but figuring out where and how to start isn’t necessarily quick and easy.

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Eggplant provides user-centric, Digital Automation Intelligence solutions that enhance the quality and performance of the digital experience. Only Eggplant enables organizations to test, monitor, analyze, and report on the quality and responsiveness of software applications across different interfaces, platforms, browsers, and devices, including mobile, IoT, desktop, and mainframe.